April 2024 arXiv papers — page 80

Kansei Kanayama, Kazuaki Toyoura

First-principles molecular dynamics (FPMD) simulations were applied for the paraelectric-ferroelectric phase transition in the perovskite-type cadmium titanate, CdTiO3. Since the phase transition is reported to occur at the low temperature around 80 K, the quantum thermal bath (QTB) method was utilized in this study, which incorporates the nuclear quantum ef

Vadim Baru, Feng-Kun Guo, Christoph Hanhart, Alexey Nefediev

We demonstrate that the dip observed near the total energy of 3872 MeV in the recent cross section data from the BESIII Collaboration for $e^+e^-\to J/\psi\pi^+\pi^- $ admits a natural explanation as a coupled-channel effect: it is a consequence of unitarity and a strong $S$-wave $D\bar D^*$ attraction that generates the state $X(3872)$. We anticipate the ap

Adrien Picquenot, Tyler Holland-Ashford, Brian J. Williams

Recent simulations have shown that asymmetries in the ejecta distribution of supernova remnants (SNRs) may be a reflection of asymmetries left over from the initial supernova explosion. Thus, SNR studies provide a vital means for testing and constraining model predictions in relation to the distribution of heavy elements, which are key to improving our under

Peng Yifeng

Market fluctuations caused by overtrading are important components of systemic market risk. This study examines the effect of investor sentiment on intraday overtrading activities in the Chinese A-share market. Employing high-frequency sentiment indices inferred from social media posts on the Eastmoney forum Guba, the research focuses on constituents of the

Xin Tan, Xiao Long, Xianjun Ni, Yinghao Zhu

Recent In-IDE AI coding assistant tools (ACATs) like GitHub Copilot have significantly impacted developers' coding habits. While some studies have examined their effectiveness, there lacks in-depth investigation into the actual assistance process. To bridge this gap, we simulate real development scenarios encompassing three typical types of software developm

Yongcheng Zeng, Guoqing Liu, Weiyu Ma, Ning Yang

Fine-tuning pre-trained Large Language Models (LLMs) is essential to align them with human values and intentions. This process often utilizes methods like pairwise comparisons and KL divergence against a reference LLM, focusing on the evaluation of full answers generated by the models. However, the generation of these responses occurs in a token level, follo

Qiyuan Dai, Sibei Yang

Referring image segmentation (RIS) aims to precisely segment referents in images through corresponding natural language expressions, yet relying on cost-intensive mask annotations. Weakly supervised RIS thus learns from image-text pairs to pixel-level semantics, which is challenging for segmenting fine-grained masks. A natural approach to enhancing segmentat

Malika Belrhazi, Tom Mestdag

For a Lagrangian system with nonholonomic constraints, we construct extensions of the equations of motion to sets of second-order ordinary differential equations. In the case of a purely kinetic Lagrangian, we investigate the conditions under which the nonholonomic trajectories are geodesics of a Riemannian metric, while preserving the constrained Lagrangian

Songtao Huang, Hongjin Song, Tianqi Jiang, Akbar Telikani

Accurate traffic forecasting is essential for effective urban planning and congestion management. Deep learning (DL) approaches have gained colossal success in traffic forecasting but still face challenges in capturing the intricacies of traffic dynamics. In this paper, we identify and address this challenges by emphasizing that spatial features are inherent

Yongfeng Huang, Zhendong Chen, Kun Ye, Lang Zhou

In this letter, we investigate a new generalized double Pareto based on off-grid sparse Bayesian learning (GDPOGSBL) approach to improve the performance of direction of arrival (DOA) estimation in underdetermined scenarios. The method aims to enhance the sparsity of source signal by utilizing the generalized double Pareto (GDP) prior. Firstly, we employ a fi

Julian Mak, Nili Harnik, Eyal Heifetz, Gautam Kumar

One mechanistic interpretation of baroclinic instability is that of mutual constructive interference of Rossby edge-waves. While the two edge-waves and their relative phase-shifts are invoked as part of the mechanistic interpretation, the phase-tilts of the related normal modes are often presented instead. Here we highlight the differences between edge-wave

Sleiman Farah, Neeraj Bokde, Gorm Bruun Andresen

Green hydrogen is essential for producing renewable fuels that are needed in sectors that are hard to electrify directly. Hydrogen production in a grid-connected hybrid renewable energy plant necessitates smart planning to meet long-term hydrogen trading agreements while minimising costs and emissions. Previous research analysed economic and environmental im

Xun Ji, Qin Liu, Shan Huang, Andi Chen

Quantum network is an emerging type of network structure that leverages the principles of quantum mechanics to transmit and process information. Compared with classical data reconstruction algorithms, quantum networks make image reconstruction more efficient and accurate. They can also process more complex image information using fewer bits and faster parall

Shunpan Liang, Junjie Zhao, Chen Li, Yu Lei

Multi-behavioral recommendation optimizes user experiences by providing users with more accurate choices based on their diverse behaviors, such as view, add to cart, and purchase. Current studies on multi-behavioral recommendation mainly explore the connections and differences between multi-behaviors from an implicit perspective. Specifically, they directly

Yawei Wei, Xiaodong Zhou

In this paper, we study Pohozaev identities, Kelvin transformation and their applications of semilinear Grushin equation. First, we establish two Pohozaev identities generated from translations and determine the location of the concentration point for solution of a kind of Grushin equation by such identities. Next, we establish Pohozaev identity generated fr

A. Svarc, R. L. Workman

Single-energy partial-wave analysis has often been applied as a way to fit data with minimal model dependence. However, remaining unconstrained, partial waves at neighboring energies will vary discontinuously because the overall amplitude phase cannot be determined through single-channel measurements. This problem can be mitigated through the use of a constr

Maria Gritsevich, Jarmo Moilanen, Jaakko Visuri, Matthias M. M. Meier

In June 1976, a pristine meteorite stone weighing approximately 1 kg, fully covered with a fresh black fusion crust, was collected on a mountain road in the high-altitude Alpine environment. The recovery took place while clearing the remnants of a snow avalanche, 2 km northwest of Ischgl in Austria. Subsequent to its retrieval, the specimen remained in the f

Madeleine I. G. Daepp, Scott Counts

The digital divide refers to disparities in access to and use of digital tooling across social and economic groups. This divide can reinforce marginalization both at the individual level and at the level of places, because persistent economic advantages accrue to places where new technologies are adopted early. To what extent are emerging generative artifici

Nicolas Ugrinovic, Boxiao Pan, Georgios Pavlakos, Despoina Paschalidou

We introduce MultiPhys, a method designed for recovering multi-person motion from monocular videos. Our focus lies in capturing coherent spatial placement between pairs of individuals across varying degrees of engagement. MultiPhys, being physically aware, exhibits robustness to jittering and occlusions, and effectively eliminates penetration issues between

Duk-Soon Oh, Shangyou Zhang

This paper introduces a novel approach to analyzing overlapping Schwarz methods for N\'{e}d\'{e}lec and Raviart--Thomas vector field problems. The theory is based on new regular stable decompositions for vector fields that are robust to the topology of the domain. Enhanced estimates for the condition numbers of the preconditioned linear systems are derived,

Teruaki Nagasawa, Kohtaro Kato, Eyuri Wakakuwa, Francesco Buscemi

Observational entropy -- a quantity that unifies Boltzmann's entropy, Gibbs' entropy, von Neumann's macroscopic entropy, and the diagonal entropy -- has recently been argued to play a key role in a modern formulation of statistical mechanics. Here, relying on algebraic techniques taken from Petz's theory of statistical sufficiency and on a L\'evy-type concen

Ayanendu Dutta, Dhritimalya Roy, Subenoy Chakraborty

The present work investigates the general wormhole solution in Einstein gravity with an exponential shape function around an ultrastatic and a finite redshift geometry. The geodesic motion around the wormholes is studied in which the deflection angle of the orbiting photon sphere is found to be negative after a certain region, indicating the presence of repu

Eduard Feireisl, Mária Lukáčová-Medvid'ová, Hana Mizerová, Changsheng Yu

We show several results on convergence of the Monte Carlo method applied to consistent approximations of the isentropic Euler system of gas dynamics with uncertain initial data. Our method is based on combination of several new concepts. We work with the dissipative weak solutions that can be seen as a universal closure of consistent approximations. Further,

Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang

In recommender systems, most graph-based methods focus on positive user feedback, while overlooking the valuable negative feedback. Integrating both positive and negative feedback to form a signed graph can lead to a more comprehensive understanding of user preferences. However, the existing efforts to incorporate both types of feedback are sparse and face t

Chongjie Si, Xuehui Wang, Xiaokang Yang, Wei Shen

Weakly Incremental Learning for Semantic Segmentation (WILSS) leverages a pre-trained segmentation model to segment new classes using cost-effective and readily available image-level labels. A prevailing way to solve WILSS is the generation of seed areas for each new class, serving as a form of pixel-level supervision. However, a scenario usually arises wher

Adva Baratz, Galit Cohen, Sivan Refaely-Abramson

Understanding complex quantum dynamics in realistic materials requires insight into the underlying correlations dominating the interactions between the participating particles. Due to the wealth of information involved in these processes, applying artificial intelligence methods is compelling. Yet, unsupervised data-driven approaches typically focus on maxim

Wenhao Zhang, Jun Wang, Yong Luo, Lei Yu

Lip-reading is to utilize the visual information of the speaker's lip movements to recognize words and sentences. Existing event-based lip-reading solutions integrate different frame rate branches to learn spatio-temporal features of varying granularities. However, aggregating events into event frames inevitably leads to the loss of fine-grained temporal inf

Zhengwei Tao, Xiancai Chen, Zhi Jin, Xiaoying Bai

Events refer to specific occurrences, incidents, or happenings that take place under a particular background. Event reasoning aims to infer events according to certain relations and predict future events. The cutting-edge techniques for event reasoning play a crucial role in various natural language processing applications. Large language models (LLMs) have

René Helmke, Elmar Padilla, Nils Aschenbruck

Firmware corpora for vulnerability research should be scientifically sound. Yet, several practical challenges complicate the creation of sound corpora: Sample acquisition, e.g., is hard and one must overcome the barrier of proprietary or encrypted data. As image contents are unknown prior analysis, it is hard to select high-quality samples that can satisfy s

Lilac Atassi

While many topics of the learning-based approach to automated music generation are under active research, musical form is under-researched. In particular, recent methods based on deep learning models generate music that, at the largest time scale, lacks any structure. In practice, music longer than one minute generated by such models is either unpleasantly r

Ping Li, Yong-qiang Liu, Jiang-he Yang, Siwei Xu

In this paper, we extend Chandrasekhar's method of calculating rotating black holes into $f(R)$ theory. We consider the Ricci scalar is a constant and derive the Kerr and Kerr-Ads metric by using the analytical mathematical method. Suppose that the spacetime is a 4-dimensional Riemannian manifold with a general stationary axisymmetric metric, we calculate Ca

Robert Jöchl, Andreas Uhl

The goal of temporal image forensic is to approximate the age of a digital image relative to images from the same device. Usually, this is based on traces left during the image acquisition pipeline. For example, several methods exist that exploit the presence of in-field sensor defects for this purpose. In addition to these 'classical' methods, there is also

Ulrich Faigle

Systems of cooperation and interaction are usually studied in the context of real or complex vector spaces. Additional insight, however, is gained when such systems are represented in vector spaces with multiplicative structures, i.e., in algebras. Algebras, on the other hand, are conveniently viewed as polynomial algebras. In particular, basic interpretatio

Milad Moradi, Ke Yan, David Colwell, Matthias Samwald

This critical review provides an in-depth analysis of Large Language Models (LLMs), encompassing their foundational principles, diverse applications, and advanced training methodologies. We critically examine the evolution from Recurrent Neural Networks (RNNs) to Transformer models, highlighting the significant advancements and innovations in LLM architectur

Hyuhng Joon Kim, Youna Kim, Cheonbok Park, Junyeob Kim

In interactions between users and language model agents, user utterances frequently exhibit ellipsis (omission of words or phrases) or imprecision (lack of exactness) to prioritize efficiency. This can lead to varying interpretations of the same input based on different assumptions or background knowledge. It is thus crucial for agents to adeptly handle the

I. A. Taimanov

We give a description of finite-zone PT-potentials in terms of explicit theta functional formulas.

Deepak Gothwal

In this paper, we introduce two moduli of w*-semidenting points and characterise the Mazur Intersection Property (MIP) and the Uniform MIP (UMIP) in terms of these moduli. We show that a property slightly stronger than UMIP already implies uniform convexity of the dual. This may lead to a possible approach towards answering the long standing open question wh

Albert Visser, Tadeusz Litak

We study the principle phi implies box phi, known as `Strength' or `the Completeness Principle', over the constructive version of L\"ob's Logic. We consider this principle both for the modal language with the necessity operator and for the modal language with the Lewis arrow, where L\"ob's Logic is suitably adapted. Central insights of provability logic, lik

Chuanhao Xu, Jingwei Cheng, Fu Zhang

Entity alignment (EA) aims to find equivalent entities between two Knowledge Graphs. Existing embedding-based EA methods usually encode entities as embeddings, triples as embeddings' constraint and learn to align the embeddings. However, the details of the underlying logical inference steps among the alignment process are usually omitted, resulting in inadeq

Liwei Lu, Ruimeng Hu, Xu Yang, Yi Zhu

This paper focuses on multi-agent stochastic differential games for jump-diffusion systems. On one hand, we study the multi-agent game for optimal investment in a jump-diffusion market. We derive constant Nash equilibria and provide sufficient conditions for their existence and uniqueness for exponential, power, and logarithmic utilities, respectively. On th

Arezoo Zohrabi, Pasha Zusmanovich

We compute $\delta$-derivations of simple Jordan algebras with values in irreducible bimodules. They turn out to be either ordinary derivations ($\delta = 1$), or scalar multiples of the identity map ($\delta = \frac 12$). This can be considered as a generalization of the "First Whitehead Lemma" for Jordan algebras which claims that all such ordinary derivat

Kislaya Ravi, Vladyslav Fediukov, Felix Dietrich, Tobias Neckel

One of the main challenges in surrogate modeling is the limited availability of data due to resource constraints associated with computationally expensive simulations. Multi-fidelity methods provide a solution by chaining models in a hierarchy with increasing fidelity, associated with lower error, but increasing cost. In this paper, we compare different mult

Alex Sheng

We develop a simple and straightforward methodology to create AI computer agents that can carry out diverse computer tasks and self-improve by developing tools and augmentations to enable themselves to solve increasingly complex tasks. As large language models (LLMs) have been shown to benefit from non-parametric augmentations, a significant body of recent w

Sonia Velasco

We introduce an interacting particle system which models the inherited sterility method. Individuals evolve on $\mathbb{Z}^d$ according to a contact process with parameter $\lambda>0$. With probability $p \in [0,1]$ an offspring is fertile and can give birth to other individuals at rate $\lambda$. With probability $1-p$, an offspring is sterile and blocks th

Chao Zhou, Huishuai Zhang, Jiang Bian, Weiming Zhang

This paper addresses the contentious issue of copyright infringement in images generated by text-to-image models, sparking debates among AI developers, content creators, and legal entities. State-of-the-art models create high-quality content without crediting original creators, causing concern in the artistic community. To mitigate this, we propose the \copy

Yuchen Tian, Ari R. Ortiz Moreno, Mayeul Chipaux, Kaiqi Wu

Diamond is increasingly popular because of its unique material properties. Diamond defects called nitrogen vacancy (NV) centers allow measurements with unprecedented sensitivity. However, to achieve ideal sensing performance NV centers need to be within nanometers from the surface and are thus strongly dependent on the local surface chemistry. Several attemp

Fang Guo, Wenyu Li, Honglei Zhuang, Yun Luo

The most recent pointwise Large Language Model (LLM) rankers have achieved remarkable ranking results. However, these rankers are hindered by two major drawbacks: (1) they fail to follow a standardized comparison guidance during the ranking process, and (2) they struggle with comprehensive considerations when dealing with complicated passages. To address the

Lalitesh Kumar, Jian Chen, Chengshuai Wu, Yuzhu Chen

This paper proposes an extended interconnection and damping assignment passivity-based control technique (IDA-PBC) to control the pressure dynamics in the fuel delivery subsystem (FDS) of proton exchange membrane fuel cells. The fuel cell stack is a distributed parameter model which can be modeled by partial differential equations PDEs). In this paper, the s

Song Wang, Jiawei Yu, Wentong Li, Wenyu Liu

Semantic scene completion, also known as semantic occupancy prediction, can provide dense geometric and semantic information for autonomous vehicles, which attracts the increasing attention of both academia and industry. Unfortunately, existing methods usually formulate this task as a voxel-wise classification problem and treat each voxel equally in 3D space

Cheng Shi, Sibei Yang

Foundation models, pre-trained on a large amount of data have demonstrated impressive zero-shot capabilities in various downstream tasks. However, in object detection and instance segmentation, two fundamental computer vision tasks heavily reliant on extensive human annotations, foundation models such as SAM and DINO struggle to achieve satisfactory performa

Abhishek Grewal, Christopher C. Leon, Olle Gunnarsson

In scanning tunneling microscopy of molecules, an insulating buffer layer is often introduced to reduce interactions between adsorbed molecules and the substrate. Focusing on tunneling through the molecule's electronic transport gap, we demonstrate that the buffer itself strongly influences the wave function of the tunneling electron at the molecule. This is

Ngoc Han Tu, Donghoon Kim, Minsoo L. Kim, Jeongmin Shim

Quantitative analysis of quantum many-body systems, consisting of numerous itinerant electrons that interact with localized spins or electrons, is a long-standing issue. The Kondo cloud, a quantum many-body object of conduction electrons that screens a single localized spin, is the building block of such strongly correlated electronic systems. While quantita

Mohammad R. Garousi

In this paper, our focus is on exploring the gauge-invariant basis for bosonic couplings within the framework of heterotic string theories, specifically examining 3-, 5-, and 7-derivative terms. We thoroughly analyze the invariance of these couplings under T-duality transformations and make a notable observation: the T-duality constraint enforces the vanishi

Zhuangzhuang Chen, Narayanan Rengaswamy

The standard approach to universal fault-tolerant quantum computing is to develop a general purpose quantum error correction mechanism that can implement a universal set of logical gates fault-tolerantly. Given such a scheme, any quantum algorithm can be realized fault-tolerantly by composing the relevant logical gates from this set. However, we know that qu

Mamutjan Ababekri, Jun-Lin Zhou, Ren-Tong Guo, Yong-Zheng Ren

Ultrarelativistic vortex leptons with intrinsic orbital angular momenta (OAM) have important applications in high energy particle physics, nuclear physics, astrophysics, etc. However, unfortunately, their generation still poses a great challenge. Here, we put forward a novel method for generating ultrarelativistic vortex positrons and electrons through nonli

Lorella Bonaccorsi, Ugo Santosuosso, Massimo Gulisano, Luca Sodini

This study investigates the efficacy of adapted boxing, specifically Rock Steady Boxing, in mitigating dopamine decline in individuals with Parkinson disease. The research involved 40 participants with confirmed diagnosis of Parkinson disease who underwent biweekly RSB sessions over an 8 week period. Training regimen included activation, core exercise, and a

Jiucai Wang, Wen Sun, Hao-Xin Wang, Zhaoyu Han

A robust theory of the mechanism of pair density wave (PDW) superconductivity (i.e. where Cooper pairs have nonzero center of mass momentum) remains elusive. Here we explore the triangular lattice $t$-$J$-$V$ model, a low-energy effective theory derived from the strong-coupling limit of the Holstein-Hubbard model, by large-scale variational Monte Carlo simul

Nakul Sharma, Aditay Tripathi, Anirban Chakraborty, Anand Mishra

In this work, we study the task of sketch-guided image inpainting. Unlike the well-explored natural language-guided image inpainting, which excels in capturing semantic details, the relatively less-studied sketch-guided inpainting offers greater user control in specifying the object's shape and pose to be inpainted. As one of the early solutions to this task

Yuanhong Qu, Bing Zhang

Growing observations of temporal, spectral, and polarization properties of fast radio bursts (FRBs) indicate that the radio emission of the majority of bursts is likely produced inside the magnetosphere of its central engine, likely a magnetar. We revisit the idea that FRBs are generated via coherent inverse Compton scattering (ICS) off low-frequency X-mode

Shijie Fang, Qianhan Feng, Tong Lin

Despite the progress of Semi-supervised Learning (SSL), existing methods fail to utilize unlabeled data effectively and efficiently. Many pseudo-label-based methods select unlabeled examples based on inaccurate confidence scores from the classifier. Most prior work also uses all available unlabeled data without pruning, making it difficult to handle large am

Xiao Wang, Ke Tang, Xingyuan Dai, Jintao Xu

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, thi

Ruoqi Zhao, Xingbang Yan, Yubo Fan

Powered hip exoskeletons have shown the ability for locomotion assistance during treadmill walking. However, providing suitable assistance in real-world walking scenarios which involve changing terrain remains challenging. Recent research suggests that forecasting the lower limb joint's angles could provide target trajectories for exoskeletons and prostheses

Yilin Zhang, Cai Xu, Han Jiang, Ziyu Guan

Multi-view learning methods often focus on improving decision accuracy while neglecting the decision uncertainty, which significantly restricts their applications in safety-critical scenarios. To address this, trusted multi-view learning methods estimate prediction uncertainties by learning class distributions from each instance. However, these methods heavi

Bo Pan, Jiaying Lu, Ke Wang, Li Zheng

The potential of automatic task-solving through Large Language Model (LLM)-based multi-agent collaboration has recently garnered widespread attention from both the research community and industry. While utilizing natural language to coordinate multiple agents presents a promising avenue for democratizing agent technology for general users, designing coordina

Riccardo Franceschi, Thomas Henning, Benoît Tabone, Giulia Perotti

This work aims to measure the mass accretion rate, the accretion luminosity, and more generally the physical conditions of the warm emitting gas in the inner disk of the very low-mass star 2MASS-J16053215-1933159. We investigate the source mid-infrared spectrum for atomic and molecular hydrogen line emission. We present the full James Webb Space Telescope (J

Peiwen Jiang, Chao-Kai Wen, Xiao Li, Shi Jin

Satellite communications can provide massive connections and seamless coverage, but they also face several challenges, such as rain attenuation, long propagation delays, and co-channel interference. To improve transmission efficiency and address severe scenarios, semantic communication has become a popular choice, particularly when equipped with foundation m

András Szenes, Dávid Vass, Balázs Bánhelyi, Mária Csete

The geometry of various plasmonic nanoantennae was numerically optimized to maximize their sensitivity to the carrier envelope phase (CEP) of the exciting ultra-short laser pulses. To verify the CEP sensitivity, the near-field response of the investigated nanoantennae was analyzed by combining frequency and time-domain numerical computations. The simulation

Ranjini Swaminathan, Jacob Schewe, Jeremy Walton, Klaus Zimmermann

Climate risk assessments must account for a wide range of possible futures, so scientists often use simulations made by numerous global climate models to explore potential changes in regional climates and their impacts. Some of the latest-generation models have high effective climate sensitivities or EffCS. It has been argued these so-called hot models are u

Zhuojia Wu, Qi Zhang, Duoqian Miao, Kun Yi

Multimodal Sentiment Analysis (MSA) aims to identify speakers' sentiment tendencies in multimodal video content, raising serious concerns about privacy risks associated with multimodal data, such as voiceprints and facial images. Recent distributed collaborative learning has been verified as an effective paradigm for privacy preservation in multimodal tasks.

Rudina Subaih, Antoine Tordeux, Mohcine Chraibi

This paper offers a comprehensive examination of single-file experiments within the field of pedestrian dynamics, providing a review from both theoretical and analytical perspectives. It begins by tracing the historical context of single-file movement studies in pedestrian dynamics. The significance of understanding the fundamental relationships between dens

Thibault Castells, Hyoung-Kyu Song, Bo-Kyeong Kim, Shinkook Choi

Latent Diffusion Models (LDMs) have emerged as powerful generative models, known for delivering remarkable results under constrained computational resources. However, deploying LDMs on resource-limited devices remains a complex issue, presenting challenges such as memory consumption and inference speed. To address this issue, we introduce LD-Pruner, a novel

Yihe Liu, Xianmin Xu

The mean curvature flow describes the evolution of a surface (a curve) with normal velocity proportional to the local mean curvature. It has many applications in mathematics, science and engineering. In this paper, we develop a numerical method for mean curvature flows by using the Onsager principle as an approximation tool. We first show that the mean curva

Qiang Wan, Chunlong Wu, Xun-Jiang Luo, Shenghao Dai

Moir\'e superlattices have become an emergent solid-state platform for simulating quantum lattice models. However, in single moir\'e device, Hamiltonians parameters like lattice constant, hopping and interaction terms can hardly be manipulated, limiting the controllability and accessibility of moire quantum simulator. Here, by combining angle-resolved photoe

Jiaming Shi, Zehua Xiao

We explore compactifications of the form of three tori with a general genus and one circle in the framework of 11D supergravity. By imposing suitable gauge conditions and boundary conditions, we find that the FRW universe with four extended spacetime dimensions and seven extremely small compactified spatial dimensions emerges as a solution for the 11D superg

Geyu Lin, Bin Wang, Zhengyuan Liu, Nancy F. Chen

Multilingual proficiency presents a significant challenge for large language models (LLMs). English-centric models are usually suboptimal in other languages, particularly those that are linguistically distant from English. This performance discrepancy mainly stems from the imbalanced distribution of training data across languages during pre-training and inst

Shagun Kaushal, Sourav Bhattacharya

We investigate the entanglement generation or harvesting between two identical, comoving Unruh-DeWitt detectors in the cosmological de Sitter spacetime. The detectors are assumed to be unentangled initially. They are individually coupled to a complex scalar field, which eventually leads to coupling between themselves. Two kinds of complex scalar fields are i

K. A. Shaulskyi, S. P. Maydanyuk, V. S. Vasilevsky

Purpose: In this paper we investigated emission of bremsstrahlung photons in the scattering of protons off deuterons within the microscopic cluster models in a wide region of the beam energy from low energies up to 1.5 GeV. Methods: Three-cluster model of bremsstrahlung is constructed for such a reaction. Formalism of the model includes form factor of deuter

Walid Abdullah Al, Il Dong Yun, Yun Jung Bae

Dopamine transporter (DAT) imaging is commonly used for monitoring Parkinson's disease (PD), where striatal DAT uptake amount is computed to assess PD severity. However, DAT imaging has a high cost and the risk of radiance exposure and is not available in general clinics. Recently, MRI patch of the nigral region has been proposed as a safer and easier altern

Supriya Ovhal, Mujumdar M, Swapna P, Sreenivas P

The ISMR profoundly impacts over a billion people across the region. ISMR extremes have been linked to the ENSO and modulated by the Indian Ocean Dipole (IOD). ISMR of 2022 displayed intriguing spatial patterns: above-normal precipitation over the south peninsula and central India, normal over Northwest India, and below-normal over East and NE India. In 2022

BESIII Collaboration

Using $e^+e^-$ collision data, corresponding to an integrated luminosity of $892\,\rm pb^{-1}$ collected at center-of-mass energies from 4.84 to 4.95\,GeV with the BESIII detector, we search for the process $e^+e^-\to K^+ K^- \psi(3770)$ by reconstructing two charged kaons and one $D$ meson from $\psi(3770)$. No significant signal of $e^+e^-\to K^+ K^- \psi(

Aylecia S. Lattimer, Steven R. Cranmer

Flows driven by photons have been studied for almost a century, and a quantitative description of the radiative forces on atoms and ions is important for understanding a wide variety of systems with outflows and accretion disks, such as active galactic nuclei. Quantifying the associated forces is crucial to determining how these outflows enable interactive m

Thibault Castells, Hyoung-Kyu Song, Tairen Piao, Shinkook Choi

The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application. To tackle this challenge, recent research focuses on methods to reduce sampling steps, such as Latent Consistency Model (LCM), and on employing architectural optimizations, including pruning and knowledge distilla

Ming Cheng, Xingjian Diao, Ziyi Zhou, Yanjun Cui

The global diabetes epidemic highlights the importance of maintaining good glycemic control. Glucose prediction is a fundamental aspect of diabetes management, facilitating real-time decision-making. Recent research has introduced models focusing on long-term glucose trend prediction, which are unsuitable for real-time decision-making and result in delayed r

Attila Egri-Nagy, Chrystopher L. Nehaniv

We give a practical computer algebra implementation of the Covering Lemma for finite transformation semigroups. The lemma states that given a surjective relational morphism $(X,S)\twoheadrightarrow(Y,T)$, we can establish emulation by a cascade product (subsemigroup of the wreath product): $(X,S)\hookrightarrow (Y,T)\wr (Z,U)$. The dependent component $(Z,U)

Hans Jarett J. Ong, Brian Godwin S. Lim, Renzo Roel P. Tan, Kazushi Ikeda

Effective causal discovery is essential for learning the causal graph from observational data. The linear non-Gaussian acyclic model (LiNGAM) operates under the assumption of a linear data generating process with non-Gaussian noise in determining the causal graph. Its assumption of unmeasured confounders being absent, however, poses practical limitations. In

Weichao Liu, Jie Cheng, Chenhao Wan

Toroidal vortex, a topological structure commonly observed in nature, exist in various types such as bubbles produced by dolphins and the air flow surrounding a flying dandelion. A toroidal vortex corresponds to a spatiotemporal wave packet in the shape of a donut that propagates in the direction perpendicular to the plane of the ring. In this work, we propo

D. S. Shirokov

In this paper, we present a natural implementation of singular value decomposition (SVD) and polar decomposition of an arbitrary multivector in nondegenerate real and complexified Clifford geometric algebras of arbitrary dimension and signature. The new theorems involve only operations in geometric algebras and do not involve matrix operations. We naturally

Shun Yin Cheung, Paul D. Lasky, Eric Thrane

Gravitational-wave memory is a non-linear effect predicted by general relativity that remains undetected. We apply a Bayesian analysis framework to search for gravitational-wave memory using binary black hole mergers in LIGO-Virgo-KAGRA's third gravitational-wave transient catalogue. We obtain a Bayes factor of $\ln \text{BF}=0.01$, in favour of the no-memor

Ali Malik, Juliette Woodrow, Chao Wang, Chris Piech

One-on-one help from a teacher is highly impactful for students, yet extremely challenging to support in massive online courses (MOOCs). In this work, we present TeachNow: a novel system that lets volunteer teachers from anywhere in the world instantly provide 1:1 help sessions to students in MOOCs, without any scheduling or coordination overhead. TeachNow w

Dawei Zhan

Bayesian optimization (BO) algorithm is very popular for solving low-dimensional expensive optimization problems. Extending Bayesian optimization to high dimension is a meaningful but challenging task. One of the major challenges is that it is difficult to find good infill solutions as the acquisition functions are also high-dimensional. In this work, we pro

Nakyeong Yang, Jiwon Moon, Junseok Kim, Yunah Jang

Enabled by large-scale text corpora with huge parameters, pre-trained language models operate as multi-task experts using a single model architecture. However, recent studies have revealed that certain neurons play disproportionately important roles in solving specific tasks, suggesting that task-relevant substructures can be isolated and selectively activat

Vincent Lahoche, Dine Ousmane Samary

This paper is the last of the series investigating renormalization group aspects of stochastic random matrices, including a Wigner-like disorder. We consider the equilibrium dynamics formalism that can be merged with the Ward identities arising from the large N effective kinetics. We construct a regulator that does not break time-reversal symmetry and show t

A. N. Jourjine

We show that unlike the SM in the flavor spin theories (theories with non- Euclidean/pseudo-unitary signature of the kinematic quadratic term of the Lagrangian) the Yukawa mass matrices are not arbitrary. This restricts the possible textures of both lepton and quark flavor mixing matrices to the experimentally observed form and reduces the number of real mix

Hjalte Frellesvig, Toni Teschke

This paper combines the post-Minkowskian expansion of general relativity with the language of intersection theory. Because of the nature of the soft limit inherent to the post-Minkowskian expansion, the intersection-based approach is of enhanced utility in that theory compared to a generic quantum field theory. In the language of intersection theory, Feynman

Hanshi Sun, Zhuoming Chen, Xinyu Yang, Yuandong Tian

With large language models (LLMs) widely deployed in long content generation recently, there has emerged an increasing demand for efficient long-sequence inference support. However, key-value (KV) cache, which is stored to avoid re-computation, has emerged as a critical bottleneck by growing linearly in size with the sequence length. Due to the auto-regressi

Li-Ya Qiao, Xiu-Cai Jiang, Ze Ruan, Yu-Zhong Zhang

Twist between neighboring layers and variation of interlayer distance are two extra ways to control the physical properties of stacked two-dimensional van der Waals materials without alteration of chemical compositions or application of external fields, compared to their monolayer counterparts. In this work, we explored the dependence of the magnetic states

Chao Zhang, Ryotaro Kase

The $U(1)$ gauge-invariant scalar-vector-tensor theories, which catches five degrees of freedom, are valuable for its implications to inflation problems, generation of primordial magnetic fields, new black hole (BH) and neutron star solutions, etc. In this paper, we derive conditions for the absence of ghosts and Laplacian instabilities of nontrivial BH solu

Andrey Starikovskiy, Arthur Dogariu

A new calibration method for H-fs-TALIF is proposed, and the ratio of two-photon absorption cross-sections, $\sigma^{(2)}$, for atomic hydrogen (H) and krypton (Kr) is determined for the broadband emission of a femtosecond laser system. The estimated ratio of the two-photon absorption cross-sections for H and Kr is $\sigma^{(2)}$ for H and Kr $\sigma^{(2)}$(

Xiquan Peng, Guokuan Shao, Wenxuan Wang

In this paper, we show that the optimal fundamental estimate holds true on a weakly $1$-complete manifold with mild conditions, then we establish the weak Morse inequalities for lower energy forms on the manifold. We also study the case for $q$-convex manifolds.

Xiankun Yan, Aneta Neumann, Frank Neumann

Recently surrogate functions based on the tail inequalities were developed to evaluate the chance constraints in the context of evolutionary computation and several Pareto optimization algorithms using these surrogates were successfully applied in optimizing chance-constrained monotone submodular problems. However, the difference in performance between algor